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The textbook for the UC Berkeley Data Science course is available for free online at Computational and Inferential Thinking.It is an online textbook and appears to be created as a collection of Jupyter notebooks. Here are some of the topics covered:

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Amazon just launched ‘Machine Learning University’ to all developers. It is the same training available for internal Amazon Employees. If you are looking to learn about Amazon Web Services (AWS) offerings for data science, now might be a great time to learn. Plus, Amazon announced some new certifications for machine learning.There are 4 different learning paths available, depending upon your goals and future job aspirations:

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Reinforcement Learning: An Introductionby Rich Sutton and Andrew Barto was recently released on October 15, 2018. The authors were kind enough to put a late draft version of the book online as a PDF. If you are hoping to learn about Reinforcement Learning, this is a great place to start.

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This month, The Data Incubator is hosting another free webinar on data science. This time it features an interview with Jake Porway, founder of DataKind. Jake and DataKind are doing amazing things, so I hope you can check out the webinar.

Below are the webinar details:

Data Science in 30 Minutes: Using Data Science in the Service of Humanity

Abstract: With his non-profit, DataKind, Jake Porway connects data scientists with social causes. Picture Doctors Without Borders for data nerds—with machine learning and AI engineers parachuting in to help the UN with humanitarian tasks, like tracking virus outbreaks using mobile data. “Data is like a bucket of crude oil,” Porway says. “Potentially great, but only if someone knows how to refine it (data scientists) and someone else has vehicles that will run on it (the social sector).” In this talk, Porway discusses the strategies of DataKind, its projects and the future of big data to service humanity.

Here are the latest articles from Microsoft regarding cloud data science products and updates. This week it includes Measuring Model Goodness, a free ebook, AI discovery days, and more AI goodness.

Measuring Model Goodness – Part 2 – Measurability is an important aspect of the Team Data Science Process (TDSP) as it quantifies how good the machine learning model is for the business and helps gain acceptance from the key stakeholders. In part 1 of this series, we defined a template for …[Read More]

AI Discovery Days at a Microsoft Location Near You – Join us to learn how to start building intelligence into your solutions with the Microsoft AI platform, including pre-trained AI services like Cognitive Services and Bot Framework, as well as deep learning tools like Azure Machine Learning.[Read More]

Describe, diagnose, and predict with IoT Analytics – … in IoT Analytics Machine learning (ML) is playing an increasingly important role in IoT analytics. One could argue that the recent emergence of real-world applications of ML in manufacturing is thanks to the explosion of data, most of which we can …[Read More]